Comparing the performance of demand responsive and schedule-based feeder services of mass rapid transit: an agent-based simulation approach

This paper presents a new agent-based model able to simulate innovative flexible demand responsive transport services, specifically thought to solve the last-mile problem of mass rapid transit. This is particularly needed in areas characterized by insufficient transit supply and lower sprawled demand, where new technologies have the potential to dynamically couple demand with supply. The model compares the performances of two feeder services, one with flexible routes and stops activated by the requests of users, and the other with fixed routes and stops, satisfying the same demand. The case study city is Catania (Italy), where such services could increase the ridership and coverage of a 9 km long metro line that connects the city centre to peripheral areas. Different scenarios have been analysed by comparing a set of key performance indicators based on service coverage and ridership. The first results highlight the validity of the model to identify optimal operation ranges of flexible on-demand services and pave the way for further investigation needed to understand their acceptability and economic viability.